In this paper, we introduce SonoNERFs, a novel approach that adapts Neural Radiance Fields (NeRFs) to model and understand the echolocation process in bats, focusing on the challenges posed by acoustic data interpretation without phase information. Leveraging insights from the field of optical NeRFs, our model, termed SonoNERF, represents the acoustic environment through Neural Reflectivity Fields. This model allows us to reconstruct three-dimensional scenes from echolocation data, obtained by simulating how bats perceive their surroundings through sound. By integrating concepts from biological echolocation and modern computational models, we demonstrate the SonoNERF\'s ability to predict echo spectrograms for unseen echolocation poses and effectively reconstruct a mesh-based and energy-based representation of complex scenes. Our work bridges a gap in understanding biological echolocation and proposes a methodological framework that provides a first-order model of how scene understanding might arise in echolocating animals. We demonstrate the efficacy of the SonoNERF model on three scenes of increasing complexity, including some biologically relevant prey-predator interactions.

The ability of \"target tracking,\" such as keeping a target object in sight, is crucial for various activities. However, most sensing systems experience a certain degree of delay due to information processing, which challenges accurate target tracking. The long history of studies on animal behavior has revealed several tactics for it, although a systematic understanding of how individual tactics are combined into a strategy has not been reached. This study demonstrates a multifaceted tracking strategy in animals, which mitigates the adverse delay effects with small implementation costs. Using an active-sensing bat to measure their sensing state while chasing natural prey, we found that bats use a tracking strategy by combining multiple echolocation and flight tactics. The three echolocation tactics, namely the predictive control of sensing direction accompanied by adjusting the sensing rate and angular range, produce a direct compensation effect. Simultaneously, the flight tactic, the counter maneuver, assists echolocation by stabilizing the target direction. Our simulation results demonstrate that these combined tactics improve tracking accuracy over a wide range of delay constraints. In addition, a concise rule based on the angular velocity between bats and targets explains how bats control these tactics, suggesting that bats successfully reduce the burden of multitasking management. Our findings reveal the sophisticated strategy in animals\' tracking systems and provide insights into understanding and developing efficiently integrated strategies in target tracking across various disciplines.

Bats use echolocation to navigate and hunt in darkness, and must in that process segregate target echoes from unwanted clutter echoes. Bats may do this by approaching a target at steep angles relative to the plane of the background, utilizing their directional transmission and receiving systems to minimize clutter from background objects, but it remains unknown how bats negotiate clutter that cannot be spatially avoided. Here, we tested the hypothesis that when movement no longer offers spatial release, echolocating bats mitigate clutter by calling at lower source levels and longer call intervals to ease auditory streaming. We trained five greater mouse-eared bats (Myotis myotis) to land on a spherical loudspeaker with two microphones attached. We used a phantom-echo setup, where the loudspeaker/target transmitted phantom clutter echoes by playing back the bats\' own calls at time delays of 1, 3 and 5 ms with a virtual target strength 7 dB higher than the physical target. We show that the bats successfully landed on the target, irrespective of the clutter echo delays. Rather than decreasing their source levels, the bats used similar source level distributions in clutter and control trials. Similarly, the bats did not increase their call intervals, but instead used the same distribution of call intervals across control and clutter trials. These observations reject our hypothesis, leading us to conclude that bats display great resilience to clutter via short auditory integration times and acute auditory stream segregation rather than via biosonar adjustments.

Most bats hunt insects on the wing at night using echolocation as their primary sensory modality, but nevertheless maintain complex eye anatomy and functional vision. This raises the question of how and when insectivorous bats use vision during their largely nocturnal lifestyle. Here, we test the hypothesis that the small insectivorous bat, Myotis daubentonii, relies less on echolocation, or dispenses with it entirely, as visual cues become available during challenging acoustic noise conditions. We trained five wild-caught bats to land on a spherical target in both silence and when exposed to broad-band noise to decrease echo detectability, while light conditions were manipulated in both spectrum and intensity. We show that during noise exposure, the bats were almost three times more likely to use multiple attempts to solve the task compared to in silent controls. Furthermore, the bats exhibited a Lombard response of 0.18 dB/dBnoise and decreased call intervals earlier in their flight during masking noise exposures compared to in silent controls. Importantly, however, these adjustments in movement and echolocation behaviour did not differ between light and dark control treatments showing that small insectivorous bats maintain the same echolocation behaviour when provided with visual cues under challenging conditions for echolocation. We therefore conclude that bat echolocation is a hard-wired sensory system with stereotyped compensation strategies to both target range and masking noise (i.e. Lombard response) irrespective of light conditions. In contrast, the adjustments of call intervals and movement strategies during noise exposure varied substantially between individuals indicating a degree of flexibility that likely requires higher order processing and perhaps vocal learning.

Achieving autonomous operation in complex natural environment remains an unsolved challenge. Conventional engineering approaches to this problem have focused on collecting large amounts of sensory data that are used to create detailed digital models of the environment. However, this only postpones solving the challenge of identifying the relevant sensory information and linking it to action control to the domain of the digital world model. Furthermore, it imposes high demands in terms of computing power and introduces large processing latencies that hamper autonomous real-time performance. Certain species of bats that are able to navigate and hunt their prey in dense vegetation could be a biological model system for an alternative approach to addressing the fundamental issues associated with autonomy in complex natural environments. Bats navigating in dense vegetation rely on clutter echoes, i.e. signals that consist of unresolved contributions from many scatters. Yet, the animals are able to extract the relevant information from these input signals with brains that are often less than 1 g in mass. Pilot results indicate that information relevant to location identification and passageway finding can be directly obtained from clutter echoes, opening up the possibility that the bats\' skill can be replicated in man-made autonomous systems.

Tiger moth species vary greatly in the number of clicks they produce and the resultant duty cycle. Signals with higher duty cycles are expected to more effectively interfere with bat sonar. However, little is known about the minimum duty cycle of tiger moth signals for sonar jamming. Is there a threshold that allows us to classify moths as acoustically aposematic versus sonar jammers based on their duty cycles? We performed playback experiments with three wild-caught adult male bats, Eptesicus fuscus. Bat attacks on tethered moths were challenged using acoustic signals of Bertholdia trigona with modified duty cycles ranging from 0 to 46%. We did not find evidence for a duty cycle threshold; rather, the ability to jam the bat\'s sonar was a continuous function of duty cycle consistent with a steady increase in the number of clicks arriving during a critical signal processing time window just prior to the arrival of an echo. The proportion of successful captures significantly decreased as the moth duty cycle increased. Our findings suggest that moths cannot be unambiguously classified as acoustically aposematic or sonar jammers based solely on duty cycle. Bats appear to compensate for sonar jamming by lengthening the duration of their terminal buzz and they are more successful in capturing moths when they do so. In contrast to previous findings for bats performing difficult spatial tasks, the number of sonar sound groups decreased in response to high duty cycles and did not affect capture success.

Identifying behaviorally relevant sounds is a vital function of the auditory system. Echolocating bats must negotiate a wealth of sounds during navigation and foraging. They must detect relatively rare but behaviorally relevant echoes and segregate them from many unimportant background echoes. For this, the bat\'s auditory system might rely on neural deviance detection-a process influencing the excitability of a neuron depending on the frequency of occurrence of a stimulus. To investigate neural deviance detection in the auditory cortex (AC) of anesthetized bats (Phyllostomus discolor), we designed sequences of repetitive virtual echoes differing in the spectrotemporal envelope, resembling those that bats might perceive in their natural environment. A standard echo was repeatedly played 10 times in these sequences, followed by a deviant echo at the end. Time intervals between echoes within the sequences varied. Our results show that neurons in the AC of the bat P. discolor are sensitive to novel virtual echoes presented at the end of these repetitive sequences: In 49% (62/126) of cortical neurons, extracellularly recorded responses adapted to the standard echo but showed a strong response to the deviant echo presented at the end. This effect depended strongly on the time intervals between echoes, with stronger adaptation at shorter intervals. This type of response might indicate a form of neuronal deviance detection mechanism in the AC that could help the bats to detect echoes of novel and potentially important objects within a stream of homogeneous background echoes.NEW & NOTEWORTHY In this study, we show that neurons in the auditory cortex of the bat Phyllostomus discolor are sensitive to novel acoustic stimuli in the context of repetitive virtual echo sequences differing in spectrotemporal envelope. This represents a form of neuronal deviance detection that might help the bats to detect echoes of rare but relevant objects among the clutter.

The ability of certain bat species to navigate in dense vegetation based on trains of short biosonar echoes could provide for an alternative parsimonious approach to obtaining the sensory information that is needed to achieve autonomy in complex natural environments. Although bat biosonar has much lower data rates and spatial (angular) resolution than commonly used human-made sensing systems such as LiDAR or stereo cameras, bat species that live in dense habitats have the ability to reliably detect narrow passageways in foliage. To study the sensory information that the animals may have available to accomplish this, we have used a biomimetic sonar system that was combined with a camera to record echoes and synchronized images from 10 different field sites that featured narrow passageways in foliage. The synchronized camera and sonar data allowed us to create a large data set (130 000 samples) of labeled echoes using a teacher-student approach that used class labels derived from the images to provide training data for echo-based classifiers. The performance achieved in detecting passageways based on the field data closely matched previous results obtained for gaps in an artificial foliage setup in the laboratory. With a deep feature extraction neural network (VGG16) a foliage-versus-passageway classification accuracy of 96.64% was obtained. A transparent artificial intelligence approach (class-activation mapping) indicated that the classifier network relied heavily on the initial rising flank of the echoes. This finding could be exploited with a neuromorphic echo representation that consisted of times where the echo envelope crossed a certain amplitude threshold in a given frequency channel. Whereas a single amplitude threshold was sufficient for this in the previous laboratory study, multiple thresholds were needed to achieve an accuracy of 92.23%. These findings indicate that despite many sources of variability that shape clutter echoes from natural environments, these signals contain sufficient sensory information to enable the detection of passageways in foliage.

Echolocation behavior, a navigation strategy based on acoustic signals, allows scientists to explore neural processing of behaviorally relevant stimuli. For the purpose of orientation, bats broadcast echolocation calls and extract spatial information from the echoes. Because bats control call emission and thus the availability of spatial information, the behavioral relevance of these signals is undiscussable. While most neurophysiological studies, conducted in the past, used synthesized acoustic stimuli that mimic portions of the echolocation signals, recent progress has been made to understand how naturalistic echolocation signals are encoded in the bat brain. Here, we review how does stimulus history affect neural processing, how spatial information from multiple objects and how echolocation signals embedded in a naturalistic, noisy environment are processed in the bat brain. We end our review by discussing the huge potential that state-of-the-art recording techniques provide to gain a more complete picture on the neuroethology of echolocation behavior.

Echolocating bats listen for weak echoes to navigate and hunt, which makes them prone to masking from background noise and jamming from other bats and prey. As for electrical fish that display clear spectral jamming avoidance responses (JAR), bats have been reported to mitigate the effects of jamming by shifting the spectral contents of their calls, thereby reducing acoustic interference to improve echo-to-noise ratio (ENR). Here, we tested the hypothesis that frequency-modulating bats (FM bats) employ a spectral JAR in response to six masking noise bands ranging from 15 to 90 kHz, by measuring the -3 dB endpoints and peak frequency of echolocation calls from five male Daubenton\'s bats (Myotis daubentonii) during a landing task. The bats were trained to land on a noise-generating spherical transducer surrounded by a star-shaped microphone array, allowing for acoustic localization and source parameter quantification of on-axis calls. We show that the bats did not employ spectral JAR as the peak frequency during jamming remained unaltered compared with that of silent controls (all P>0.05, 60.73±0.96 kHz, mean±s.e.m.), and -3 dB endpoints decreased in noise irrespective of treatment type. Instead, Daubenton\'s bats responded to acoustic jamming by increasing call amplitude via a Lombard response that was bandwidth dependent, ranging from a mean of 0.05 dB/dB (95% confidence interval 0.04-0.06 dB/dB) noise for the most narrowband noise (15-30 kHz) to 0.17 dB/dB (0.16-0.18 dB/dB) noise for the most broadband noise (30-90 kHz). We conclude that Daubenton\'s bats, despite having the vocal flexibility to do so, do not employ a spectral JAR, but defend ENRs via a bandwidth-dependent Lombard response.